An imaging device, such as a printer or copier, typically creates images using combinations of four colors of marking agents or colorants, such as cyan, magenta, yellow and black (CMYK). The images are created based on image data which assigns at least one of the four colors and a numerical color intensity or input color value to each picture element or pixel in the image.
A problem is that, due to manufacturing variations, different imaging devices can output different intensities of color based on identical image data. The density of the toner laid down on the print medium determines the color intensity. The denser or thicker the toner is laid down on a white print medium such as paper, the less white is visible through the toner on the paper. Consequently, the denser the toner, the less the lightness of the toner color, and the greater the intensity of the toner color.
Because there is such variation in toner density laid down by different imaging devices based on identical image data, color intensities that are output by some imaging devices can be outside of an acceptable range. Thus, in order to ensure that each imaging device outputs color intensities that closely correspond to the color intensities specified by the image data, each imaging device should be individually calibrated to output appropriate color intensities.
By way of background, traditionally, calibrating printers (e.g. any apparatus, such as a digital copier, bookmaking machine, facsimile machine, multi-function machine, etc. which performs a print outputting function for any purpose) has proven to be a less-than-efficient task, particularly if large amounts of data (e.g. test patches) are used. Recently, scanners have been contemplated as an efficient mechanism to aid in the calibration process. Traditional printer calibration (that is, not using a scanner) typically has employed a densitometer or spectrophotometer, which includes an aperture typically around 5 mm in diameter, the reflected light that passes through that aperture is optically averaged by the device. Scanner based printer calibration has traditionally involved averaging the area in some region analogous to the aperture of a spectrophotometer or densitometer.
Scanner-based printer calibration requires scanning portions of printed pages, applying some image processing technique to obtain averages over small regions of the page, in analogy to the spectrophotometer aperture, and then converting the averaged signal to a device independent color space. To do this conversion, the scanner must itself be characterized. Calibration is a process that obtains the change required to the device signals required to restore the device behavior to its nominal state; characterization is a process that obtains the conversion from device signals to device independent signals in some standardized color space.
As alluded to above, color calibration is a process of measuring the device response to a known input and deriving a compensation for deviation from an “ideal” device. Calibration typically derives a one-dimensional correction function which is applied channel-wise through lookup tables. Calibration is typically applied to spectrophotometers and scanners in the form of white point calibration. A single measurement of a known white is used to compensate for instrument drift. Some scanners have a further calibration for black point variation. Printer calibration has traditionally been either in the form of linearizing individual channels (either in density or ΔE from paper) or in the form of grey balance. Grey balance calibration derives a set of one-dimensional correction functions for cyan, magenta and yellow, which when used in concert with equal inputs produce outputs that match a desired aim, such as a*=b*=0.
In a recent improvement, U.S. Publication No. 2004/0257595 A1 to Sharma et al. (filed Jun. 18, 2003 and bearing application Ser. No. 10/465,408), which is incorporated herein by reference in its entirety introduces a two-dimensional calibration scheme in which the correction function for a given separation depends not only on the input value of that separation, but also on a scalar function of the input values of the other separations. This method allows the calibration to provide the advantages associated with both grey balance and ΔE from paper, along with some improvements in portions of color space not controlled by those techniques.
The fundamental elements of color printer calibration are:
select a set of patches to print, typically being of one size;
print the patches;
measure the patches; and
derive a correction function.
The set of patches might change in an iterative process. The measurement might involve a spectrophotometer or similar instrument. The correction function is likely to depend on the nature of the calibration: grey balance, ΔE from paper, or 2D.
Color characterization is in principle a similar process to color calibration. It is used to derive a conversion function that is then applied to input data which is then sent to the “ideal” device as produced by applying the color calibration's correction function to the actual device. This conversion function maps device independent colors from some standardized space to colors appropriate for a corrected device. One common device independent space is L*a*b*; another is standardized RGB.
At a high level, color characterization when applied to printers is the same as color printer calibration: one selects patches to print, prints and measures them, and derives a correction function. The difference is that the patches printed generally cover the gamut of the device more completely, and the correction function is normally multi-dimensional. Rather than deriving a set of scalar correction functions, a vector valued function is derived that maps three dimensional locations in color space to four dimensional printer values. This function is naturally more complex, and the derivation involves more computation, and generally requires more measured values to drive it.
Color characterization applied to scanners is only slightly different at a high level. Patches are printed on one or more printers, and measured using a well known and characterized measurement device, such as a spectrophotometer. The same patches are scanned and averaged and the correction function is derived to obtain a mapping from averaged values to values measured using the spectrophotometer. Improved results are obtained when a separate characterization is derived for each different printer type (esp. inkjet, photographic, lithographic and xerographic, but also different toner or ink sets), but average characterizations may also be derived for use when the printer type is unknown.
Given a characterized scanner, especially one characterized for a particular type of printer, that scanner may be used to characterize or calibrate an instance of that printer. In that case, the printer would generate the patches, the scanner would scan them, and they would be averaged and converted to device independent color space. From here on the process would follow the same pattern as for spectrophotometer based calibration or characterization, provided the algorithms used do not rely on the spectral data available from a spectrophotometer, and only rely on the L*a*b* values.
However, printers exhibit different amounts of noise depending on the level, as do scanners. Even noise in spectrophotometers appears to have some dependence on input level. Treating all levels equally leads to a compromise between over-measuring low-noise regions and under-measuring high noise regions. This disadvantage is realized where only a single size test patch is used in the calibration or characterization process. The variance resulting from analysis of such patches skews the results and leads to a less-effective calibration or characterization. An alternative is to use weighted least squares fitting to penalize bad fits in areas of more reliable data; however, this produces no guarantee that the fit will be any better in the high noise regions.